Machine Learning Research Engineer - Trading

Selby Jennings; New York (NY); On-site; USD 200,000 - 250,000; Full time

Job summary

A leading financial recruitment firm, Selby Jennings, seeks a Machine Learning Research Engineer specializing in deep learning methodologies to enhance trading strategies. The role includes constructing pipelines and collaborating across teams, ideally suited for candidates with strong programming skills in C++ and Python.

Benefits

Annual Bonus

Sign-on Bonus

Qualifications

• Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow.
• Thorough knowledge of computer architecture.
• Proficiency for developing scalable solutions.

Responsibilities

• Constructing scalable training and inference pipelines for deep learning.
• Collaborating closely with researchers and fellow engineers.
• Resolving performance bottlenecks.

Skills

Proficiency in deep learning frameworks

Programming in C++

Programming in Python

Job description

Machine Learning Research Engineer - Trading

Machine Learning Research Engineer - Trading

This range is provided by Selby Jennings. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$200,000.00/yr - $250,000.00/yr

Additional compensation types

Annual Bonus and Sign-on bonus

Direct message the job poster from Selby Jennings

FinTech Headhunter | Prop Trading and Hedge Funds

We are currently partnered with several leading hedge funds and proprietary trading firms that are actively seeking talented Machine Learning Research Engineers. In this role, you will engage in cutting-edge research and play a key part in implementing advanced machine learning solutions to drive their trading strategies.

Your Responsibilities:

• Constructing scalable and resilient training and inference pipelines for deep learning.
• Delving into the inner workings of open-source deep learning frameworks to enhance their capabilities.
• Identifying and resolving performance bottlenecks.
• Collaborating closely with researchers and fellow engineers.
• Developing a comprehensive understanding of trading systems.

Requirements:

• Proficiency in the inner workings of deep-learning frameworks such as PyTorch, JAX, TensorFlow, etc.
• Thorough knowledge of computer architecture.
• Proficiency in programming with C++ and Python.

Preferred Qualifications:

• Experience with the JAX ecosystem, including XLA, Flax, etc.
• Proficiency in programming for GPUs or other accelerators like CUDA, Triton, Pallas, etc.
• Experience in Linux system programming.
• Familiarity with large-scale distributed training.
• Contributions to open-source projects in the realm of data science and machine learning.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering, Finance, and Information Technology

• Industries

  Capital Markets and Financial Services

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